EP1529249A2 - Procede et ensemble permettant la conception d'un systeme technique - Google Patents
Procede et ensemble permettant la conception d'un systeme techniqueInfo
- Publication number
- EP1529249A2 EP1529249A2 EP03790663A EP03790663A EP1529249A2 EP 1529249 A2 EP1529249 A2 EP 1529249A2 EP 03790663 A EP03790663 A EP 03790663A EP 03790663 A EP03790663 A EP 03790663A EP 1529249 A2 EP1529249 A2 EP 1529249A2
- Authority
- EP
- European Patent Office
- Prior art keywords
- determined
- predictor
- points
- variable
- space
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 91
- 230000006870 function Effects 0.000 claims abstract description 19
- 238000013461 design Methods 0.000 claims abstract description 11
- 239000013598 vector Substances 0.000 claims description 16
- 230000005653 Brownian motion process Effects 0.000 claims description 6
- 238000005537 brownian motion Methods 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 4
- 239000011159 matrix material Substances 0.000 claims description 4
- 238000003860 storage Methods 0.000 claims description 2
- 238000005309 stochastic process Methods 0.000 claims 1
- 238000005457 optimization Methods 0.000 description 10
- 238000011161 development Methods 0.000 description 3
- 230000018109 developmental process Effects 0.000 description 3
- 230000003993 interaction Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000001028 reflection method Methods 0.000 description 2
- 101100290182 Mus musculus Mas1 gene Proteins 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000033001 locomotion Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000010561 standard procedure Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
- 238000009827 uniform distribution Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
- G05B13/024—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a parameter or coefficient is automatically adjusted to optimise the performance
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
- G05B13/026—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system using a predictor
Definitions
- the invention relates to a method and an arrangement for designing a technical system.
- a weighting method for optimizing technical systems with regard to several criteria is known from [1], in which transformations are applied to scalar-value optimization problems with the aid of scaling parameters.
- This method has the disadvantage that it is numerically very complex since a large number of scalar value optimizations have to be carried out.
- the selection and variation of the scaling parameters requires interaction with a user and cannot be automated in this regard.
- [2] describes a stochastic method for the optimization of technical systems with regard to several criteria, in which a stochastic differential equation is used to solve the Optimization problem is used.
- This method has the disadvantage that it is numerically very complex since a large number of quadratic optimization problems have to be solved.
- Another disadvantage is that with this method the individual target functions are not weighted, which means that the user does not have access to important information on the selection of an optimal point.
- a homotopy method for optimizing technical systems with regard to several criteria is known from [3], in which, in addition to weighting factors for the target functions, Lagrangian multipliers are also used to take account of secondary conditions.
- Lagrangian multipliers are also used to take account of secondary conditions.
- the disadvantage of this method is that an interaction with the user is necessary and this method cannot be automated in this regard.
- the invention is therefore based on the object of creating an automated and numerically efficient method for designing a technical system.
- the technical system is modeled by a predetermined set of target functions that depend on parameters. Each individual objective function is weighted with a weighting factor.
- the method solves an equation system comprising the parameters and the weighting factors as variables in a variable space, solutions of the system of equations forming working points of a solution space in the variable space.
- the operating points are determined by means of a predictor-corrector method in which, starting from a first operating point, a predictor which is generated by means of a stochastic variable is determined in the variable space and finally a second operating point is determined in a correction step.
- the determined working points are used for the design of the technical system.
- the design of the technical system can be a new design or a change or adaptation of an existing technical system.
- the predictor is specified by means of random numbers, so that a random number generator can be used in particular when the method is running and thus the automation of the method is ensured in a simple manner.
- the random numbers are normally distributed. This ensures that the trajectory of working points, which is formed in the solution space when the method is run, ensures uniform distribution and thus good coverage of all possible working points in the entire solution space.
- normally distributed random numbers By using normally distributed random numbers, a Brownian motion in the solution space can be modeled with the method according to the invention.
- the working points which are determined by the method according to the invention are preferably so-called pareto-optical points which can no longer be further optimized in relation to all target functions.
- the points with positive weighting factors in the solution space are selected as working points.
- the operating points must also meet one or more secondary conditions, the or each secondary condition being represented by a further variable of the system of equations in the variable space.
- the constraints can be equality constraints and / or inequality constraints.
- inequality constraints a slip variable is preferably introduced with which the inequality constraints can be converted into equality constraints. The use of slip variables is explained in more detail in the detailed description of an exemplary embodiment.
- the solution space of the working points is preferably a manifold, in particular a sub-manifold in the variable space. [3] explains the conditions under which the solution space forms such a diversity.
- this first valid working point is determined by a weighting method, the use of weighting methods already being known from the prior art (see [1]) ,
- Tangential plane to the solution space is determined, and then the predictor is determined in this tangential plane.
- a new predictor when a negative predictor with one or more negative weighting factors occurs, a new predictor is reflected by a reflection at a sublevel of the solution space. determined working points. In this way, new regions of valid working points can be determined, these working points being of particular relevance for the user with regard to secret additional criteria or his expert knowledge.
- an intersection of the trajectory, which runs between the first working point and the negative predictor, with a sub-level of the solution space is determined in the reflection step.
- the tangential component of the vector spanned by the intersection and the negative predictor to the relevant sub-level of the solution space is determined, the weighting factors in the points of the sub-level that were negative for the negative predictor now being zero.
- the normal component of the vector spanned by the intersection and the negative predictor belonging to this tangential component is then determined. Finally, the new predictor is determined by subtracting the normal part twice from the negative predictor.
- the operating points are preferably determined by iterations of the predictor-corrector method, the second operating point of the previous iteration step being used as the first operating point of the predictor-corrector method in one iteration step.
- the method is ended, for example, by an abort condition.
- the termination condition is met when a predetermined number of operating points has been determined and / or a predetermined time limit has been reached.
- the invention also relates to an arrangement for designing a technical system with which the method described above can be carried out.
- the method comprises a processor unit with which it is possible that the predictor can be generated by means of a stochastic variable.
- the arrangement preferably comprises a random number generator for generating random numbers which represent the stochastic variable.
- the invention or any further development described above can also be implemented by a computer program product which has a storage medium on which a computer program is stored which can be run on a computer and which carries out the invention.
- Fig.l is a flowchart of the inventive method for designing a technical system
- Figure 3 is a sketch illustrating the reflection method used in a modification of the invention
- FIG. 4 shows a processor unit for carrying out the method according to the invention.
- 1 shows a flowchart of the method according to the invention for designing a technical system.
- a description form of the technical system is selected in step 101.
- the target functions are, for example, the investment costs fi and the efficiency f of the technical system.
- the objective functions in this case are described by the following equation
- the parameters xi to x n can be design parameters or operating parameters of the technical system.
- the valid working points used for the design of the technical system are determined by optimizing the target functions with regard to the parameters, wherein not all target functions fi to f k can be optimized at the same time, since the optimization criteria generally compete with one another stand.
- the valid working points are so-called pareto-optimal points, which meet the following condition:
- the secondary conditions are determined by the Lagrangian
- the solutions to the optimization problem are therefore vectors (x, ⁇ , ⁇ ) in the (n + m + k) -dimensional variable space of the system of equations above.
- a first pareto-optimal point z is determined using a standard method, e.g. the weighting method.
- a (k-1) -dimensional tangential plane T Z M to the manifold M of the valid working points at point z is determined in the next step 103.
- a Jacobi matrix of the system of equations F is subjected to QR factorization at point z. From this, an orthonormal basis ⁇ q ⁇ ... qk- ⁇ is determined, which spans the tangential plane.
- the individual numerical steps performed here are described in detail in [3].
- a predictor y is determined in this tangential plane, the predictor - in contrast to the homotopy method described in [3] - by means of a normally distributed random number vector b of dimension k-1 is generated in the tangential plane.
- the predictor y has the following form:
- Brownian motion can be modeled on the sub manifold M, whereby the Brownian motion can be represented approximately as follows:
- P (z) is a projection matrix on the tangential plane T Z M at the valid working point z
- ⁇ is a scaling factor
- j G ⁇ Q is a Brownian motion in variable space.
- the k-1-dimensional normal distribution N (0 k - ⁇ , t ⁇ ⁇ I k - ⁇ ) is chosen for b, the mean value 0 k - ⁇ being the (k-1) -dimensional zero vector and the variance the (k-1) -dimensional identity matrix I k is multiplied by a step size t ⁇ of Brownian motion and the scaling factor ⁇ .
- the predictor can be determined by first determining a normally distributed random number vector in the (m + n + k) -dimensional variable space and then projecting it into the (k-1) -dimensional tangential plane T Z M. Then in step 105 the predictor is projected onto the manifold of the pareto-optimal points with the aid of a corrector method, which is for example a numerical Newton method. In this way, a new valid working point is determined on the manifold of the pareto-optimal points.
- a corrector method which is for example a numerical Newton method.
- Steps 103, 104 and 105 are repeated iteratively, the working point determined in the previous iteration step being used as the starting point for calculating a new valid working point.
- step 106 it is checked whether an abort criterion is fulfilled, i.e. whether e.g. a predetermined number of iterations has been carried out or a predetermined time limit has been reached. If this is not the case, the process returns to step 103 and the next iteration is carried out. This continues until the termination criterion is met.
- an abort criterion i.e. whether e.g. a predetermined number of iterations has been carried out or a predetermined time limit has been reached. If this is not the case, the process returns to step 103 and the next iteration is carried out. This continues until the termination criterion is met.
- step 106 If the termination criterion in step 106 is met, then in a next step 107 the set of determined pareto-optimal points is limited to those points at which the weighting factors are ⁇ positive.
- a final step 108 the user selects a working point of the technical system that is efficient for his requirements from these pareto-optimal points and the technical system is designed with this efficient working point.
- FIG. 2 shows a two-dimensional graphic representation of the predictor-corrector method used in the invention.
- z 1 denotes a pareto-optimal point on the sub-manifold M, this point being obtained in the ith iteration step of the method.
- the tangent tial plane T zi M To determine a new pareto-optimal point, the tangent tial plane T zi M to the sub manifold M at point z 1 .
- the tangential plane is indicated in FIG. 2 with dashed lines.
- a predictor point y i + 1 is then determined using normally distributed random numbers in the tangential plane T zi M.
- the new pareto-optimal point z i + 1 is then determined.
- the method is then continued, using the pareto-optimal point z 1+ ⁇ as the starting point for the new predictor step.
- FIG. 3 relates to a modification of the method according to the invention, wherein when predictors with negative weighting factors ⁇ ⁇ occur, a reflection is carried out to determine a new predictor with positive ⁇ j_.
- FIG. 3 shows the implementation of this projection step in a three-dimensional representation.
- FIG. 3 shows a case in which, starting from a pareto-optimal point z, a predictor y ne g is determined which has a negative ⁇ * j_. This is illustrated graphically by the fact that the distance between point z and point y penetrates the tangential plane T Z M at point S. The point S is again on a sub-plane of the tangential plane T Z M, for the points of which the coordinate ⁇ ⁇ has the value zero. In order to carry out the reflection, the intersection S is first determined. This can be done using a projection operator that projects the ⁇ component out of a parameter representation of the straight line passing through the points z and y. After determining the point S, the vector x neg running between S and y can now be determined.
- This vector is then broken down into the tangential component t to the sub-plane and into a normal component n.
- t Xneg-n.
- the reflection step is then carried out, the new reflected vector x new having the same tangential component t as the old vector x neg and the Normal part corresponds to the normal part n of the old vector x ne g with the opposite sign.
- the processor unit PRZE comprises a processor CPU, a memory MEM and
- IFC is used in different ways: Via a graphics interface, output is visible on a MON monitor and / or output on a PRT printer. An entry is made using a mouse MAS or a keyboard TAST.
- the processor unit PRZE also has a data bus
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE10237335A DE10237335A1 (de) | 2002-08-14 | 2002-08-14 | Verfahren und Anordnung zum Entwurf eines technischen Systems |
| DE10237335 | 2002-08-14 | ||
| PCT/DE2003/002566 WO2004021209A2 (fr) | 2002-08-14 | 2003-07-30 | Procede et ensemble permettant la conception d'un systeme technique |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| EP1529249A2 true EP1529249A2 (fr) | 2005-05-11 |
| EP1529249B1 EP1529249B1 (fr) | 2009-12-02 |
Family
ID=29719530
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP03790663A Expired - Lifetime EP1529249B1 (fr) | 2002-08-14 | 2003-07-30 | Procede et ensemble permettant la conception d'un systeme technique |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US7444312B2 (fr) |
| EP (1) | EP1529249B1 (fr) |
| JP (1) | JP4185050B2 (fr) |
| AU (1) | AU2003260249A1 (fr) |
| DE (2) | DE10237335A1 (fr) |
| WO (1) | WO2004021209A2 (fr) |
Families Citing this family (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7668707B2 (en) * | 2007-11-28 | 2010-02-23 | Landmark Graphics Corporation | Systems and methods for the determination of active constraints in a network using slack variables and plurality of slack variable multipliers |
| USRE48680E1 (en) | 2009-06-26 | 2021-08-10 | Turbonomic, Inc. | Managing resources in container systems |
| US10346775B1 (en) | 2015-11-16 | 2019-07-09 | Turbonomic, Inc. | Systems, apparatus and methods for cost and performance-based movement of applications and workloads in a multiple-provider system |
| US9888067B1 (en) | 2014-11-10 | 2018-02-06 | Turbonomic, Inc. | Managing resources in container systems |
| US8914511B1 (en) * | 2009-06-26 | 2014-12-16 | VMTurbo, Inc. | Managing resources in virtualization systems |
| US10673952B1 (en) | 2014-11-10 | 2020-06-02 | Turbonomic, Inc. | Systems, apparatus, and methods for managing computer workload availability and performance |
| US9852011B1 (en) | 2009-06-26 | 2017-12-26 | Turbonomic, Inc. | Managing resources in virtualization systems |
| US9858123B1 (en) | 2014-11-10 | 2018-01-02 | Turbonomic, Inc. | Moving resource consumers in computer systems |
| US10552586B1 (en) | 2015-11-16 | 2020-02-04 | Turbonomic, Inc. | Systems, apparatus and methods for management of computer-based software licenses |
| US9830192B1 (en) | 2014-11-10 | 2017-11-28 | Turbonomic, Inc. | Managing application performance in virtualization systems |
| US11272013B1 (en) | 2009-06-26 | 2022-03-08 | Turbonomic, Inc. | Systems, apparatus, and methods for managing computer workload availability and performance |
| US10191778B1 (en) | 2015-11-16 | 2019-01-29 | Turbonomic, Inc. | Systems, apparatus and methods for management of software containers |
| US9830566B1 (en) | 2014-11-10 | 2017-11-28 | Turbonomic, Inc. | Managing resources in computer systems using action permits |
| USRE48714E1 (en) | 2009-06-26 | 2021-08-31 | Turbonomic, Inc. | Managing application performance in virtualization systems |
| USRE48663E1 (en) | 2009-06-26 | 2021-07-27 | Turbonomic, Inc. | Moving resource consumers in computer systems |
| US9805345B1 (en) | 2014-11-10 | 2017-10-31 | Turbonomic, Inc. | Systems, apparatus, and methods for managing quality of service agreements |
| US9971668B1 (en) * | 2013-05-15 | 2018-05-15 | The United States Of America As Represented By Secretary Of The Navy | Method for identifying the performance bounds of a transmit-receive module |
| CN106296806B (zh) * | 2016-08-10 | 2019-03-22 | 河海大学 | 一种基于整体最小二乘的附加几何约束的点云建模方法 |
Family Cites Families (32)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5684713A (en) * | 1993-06-30 | 1997-11-04 | Massachusetts Institute Of Technology | Method and apparatus for the recursive design of physical structures |
| US5361628A (en) * | 1993-08-02 | 1994-11-08 | Ford Motor Company | System and method for processing test measurements collected from an internal combustion engine for diagnostic purposes |
| US5650728A (en) * | 1995-04-03 | 1997-07-22 | Hubbell Incorporated | Fault detection system including a capacitor for generating a pulse and a processor for determining admittance versus frequency of a reflected pulse |
| US5592791A (en) * | 1995-05-24 | 1997-01-14 | Radix Sytems, Inc. | Active controller for the attenuation of mechanical vibrations |
| US5615109A (en) * | 1995-05-24 | 1997-03-25 | Eder; Jeff | Method of and system for generating feasible, profit maximizing requisition sets |
| KR100205691B1 (ko) | 1997-04-29 | 1999-07-01 | 정순착 | 공정 제어용 혼성예측자 및 혼성 예측 방법 |
| US6292830B1 (en) * | 1997-08-08 | 2001-09-18 | Iterations Llc | System for optimizing interaction among agents acting on multiple levels |
| US6529934B1 (en) * | 1998-05-06 | 2003-03-04 | Kabushiki Kaisha Toshiba | Information processing system and method for same |
| EP1145171A3 (fr) * | 1998-06-17 | 2002-09-11 | Siemens Aktiengesellschaft | Procede et dispositif pour l'etablissement d'un projet de systeme technique |
| US6387034B1 (en) * | 1998-08-17 | 2002-05-14 | Georia Tech Research Corporation | Brachytherapy treatment planning method and apparatus |
| US6381505B1 (en) * | 1998-09-28 | 2002-04-30 | Aspen Technology, Inc. | Robust steady-state target calculation for model predictive control |
| US6714899B2 (en) * | 1998-09-28 | 2004-03-30 | Aspen Technology, Inc. | Robust steady-state target calculation for model predictive control |
| WO2000033209A2 (fr) * | 1998-12-03 | 2000-06-08 | Siemens Aktiengesellschaft | Procede et dispositif de conception d'un systeme technique |
| EP1190363A2 (fr) * | 1998-12-04 | 2002-03-27 | Siemens Aktiengesellschaft | Procede et dispositif pour la conception d'un systeme technique |
| WO2000065412A1 (fr) * | 1999-04-27 | 2000-11-02 | Siemens Aktiengesellschaft | Procede et dispositif pour developper un systeme technique |
| CA2373698C (fr) * | 1999-05-10 | 2011-05-31 | Siemens Aktiengesellschaft | Procede, systeme et programme informatique destines a la comparaison d'une premiere specification avec une seconde specification |
| EP1052558B1 (fr) * | 1999-05-14 | 2002-08-07 | Abb Research Ltd. | Procédé et dispositif d'estimation d' état |
| DE19932945A1 (de) * | 1999-07-14 | 2001-01-25 | Siemens Ag | Verfahren, Anordnung und Computerprogramm zur Vorverarbeitung |
| WO2001007972A1 (fr) * | 1999-07-23 | 2001-02-01 | Siemens Aktiengesellschaft | Procede et dispositif pour la conception d'un systeme technique |
| US6601233B1 (en) * | 1999-07-30 | 2003-07-29 | Accenture Llp | Business components framework |
| US6609128B1 (en) * | 1999-07-30 | 2003-08-19 | Accenture Llp | Codes table framework design in an E-commerce architecture |
| US6633878B1 (en) * | 1999-07-30 | 2003-10-14 | Accenture Llp | Initializing an ecommerce database framework |
| US6530873B1 (en) * | 1999-08-17 | 2003-03-11 | Georgia Tech Research Corporation | Brachytherapy treatment planning method and apparatus |
| US6526373B1 (en) | 1999-10-08 | 2003-02-25 | Dassault Systemes | Optimization tool for robot placement |
| US7330806B2 (en) * | 2000-08-08 | 2008-02-12 | Reohr Iii John | Virtualized network |
| JP4557397B2 (ja) * | 2000-09-05 | 2010-10-06 | 本田技研工業株式会社 | 翼形状設計方法および情報媒体 |
| JP4474814B2 (ja) * | 2001-09-05 | 2010-06-09 | 三菱電機株式会社 | 監視システム |
| US7194317B2 (en) * | 2002-08-22 | 2007-03-20 | Air Products And Chemicals, Inc. | Fast plant test for model-based control |
| CN1717636A (zh) * | 2002-11-29 | 2006-01-04 | 西门子公司 | 用于确定被测量的系统分析方法 |
| US6999884B2 (en) * | 2003-01-10 | 2006-02-14 | Oxford Biosignals Limited | Bearing anomaly detection and location |
| US7400108B2 (en) * | 2004-04-15 | 2008-07-15 | University Of Utah Research Foundation | System and method for controlling modular robots |
| US7165465B2 (en) * | 2004-09-29 | 2007-01-23 | Raytheon Company | Dynamic load fixture for application of torsion loads for rotary mechanical systems |
-
2002
- 2002-08-14 DE DE10237335A patent/DE10237335A1/de not_active Ceased
-
2003
- 2003-07-30 EP EP03790663A patent/EP1529249B1/fr not_active Expired - Lifetime
- 2003-07-30 WO PCT/DE2003/002566 patent/WO2004021209A2/fr not_active Ceased
- 2003-07-30 US US10/524,556 patent/US7444312B2/en not_active Expired - Fee Related
- 2003-07-30 AU AU2003260249A patent/AU2003260249A1/en not_active Abandoned
- 2003-07-30 JP JP2004531433A patent/JP4185050B2/ja not_active Expired - Fee Related
- 2003-07-30 DE DE50312194T patent/DE50312194D1/de not_active Expired - Lifetime
Non-Patent Citations (1)
| Title |
|---|
| See references of WO2004021209A2 * |
Also Published As
| Publication number | Publication date |
|---|---|
| EP1529249B1 (fr) | 2009-12-02 |
| WO2004021209A3 (fr) | 2004-07-01 |
| DE50312194D1 (de) | 2010-01-14 |
| US7444312B2 (en) | 2008-10-28 |
| WO2004021209A2 (fr) | 2004-03-11 |
| DE10237335A1 (de) | 2004-01-08 |
| AU2003260249A8 (en) | 2004-03-19 |
| US20050256683A1 (en) | 2005-11-17 |
| JP4185050B2 (ja) | 2008-11-19 |
| JP2005537539A (ja) | 2005-12-08 |
| AU2003260249A1 (en) | 2004-03-19 |
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